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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Focused Ion Beam Tomography of Alloy 617 Corroded in Molten Chloride Salt

Materials qualification of reactor structural materials is a critical step in rapid implementation of advanced nuclear reactor technologies, particularly to assess the corrosion performance in these designs. Accelerated qualification of reactor structural materials requires incorporating powerful computational toolsets, such as phase field modelling in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, to predict the evolution of structural materials due to corrosion. Accordingly, computational toolsets will require experimental data generated at appropriate length scales to validate accuracy. Focused ion beam (FIB) provides a high degree of control over manipulation of materials for analytical purposes, including capturing data on the evolution in the microstructure and elemental composition of materials at the mesoscale, an appropriate length scale for phase field modelling of intergranular diffusion phenomena using the MOOSE framework. For instance, the FEI Helios G4 UX dual beam plasma FIB microscope at the Irradiated Materials Characterization Laboratory (IMCL) is capable of backscatter diffraction (EBSD) and energy-dispersive x-ray spectroscopy (EDS) documenting the evolution in the microstructure and elemental composition, respectively. The Helios can perform EDS and EBSD three-dimensionally (3D) using tomography, which is then combined using different software packages to visualize 3D volumes correlating elemental composition to microstructural data. The purpose of this investigation was to develop a streamlined characterization and data processing workflow for 3D tomography studies on the FEI Helios G4 plasma FIB. The investigation is segmented into three parts: 1) Optimizing the data collection workflow, 2) identifying appropriate data processing and visualization software (i.e. DREAM.3D, MIPAR, and VGStudioMax), and 3) establishing an infrastructure for public release. The optimization of the data collection workflow is in collaboration with members of the U220 department to setup formal training on the tomography operation of the G4, through ThermoFisher Scientific, and exploring DREAM.3D, MIPAR, and VGStudioMax data processing/visualization software packages. VGStudioMax currently demonstrates the most promise for future use. Optimization of the data collection and processing workflow is still ongoing. A collaboration with INL High Performance Computing (HPC) established an open-source license for expediting the public release of FIB tomography datasets through HPC. FIB tomography data generated by the G4 will provide comprehensive data for validating 3D phase field mesoscale modelling tools within the MOOSE framework for accelerated qualification of reactor structural materials.

Copeland-Johnson, Trishelle↗
NASA NTRS1977

Technology requirements for advanced earth-orbital transportation systems: Summary report

Areas of advanced technology that are either critical or offer significant benefits to the development of future Earth-orbit transportation systems were identified. Technology assessment was based on the application of these technologies to fully reusable, single-state-to-orbit (SSTO) vehicle concepts with horizontal landing capability. Study guidelines included mission requirements similar to space shuttle, an operational capability beginning in 1995, and main propulsion to be advanced hydrogen-fueled rocket engines. The technical and economic feasibility of this class of SSTO concepts were evaluated as well as the comparative features of three operational take-off modes, which were vertical boost, horizontal sled launch, and horizontal take-off with subsequent inflight fueling. Projections of both normal and accelerated technology growth were made. Figures of merit were derived to provide relative rankings of technology areas. The influence of selected accelerated areas on vehicle design and program costs was analyzed by developing near-optimum point designs.

Haefeli, R. C.↗
NASA NTRS1977

Technology requirements for advanced earth-orbital transportation systems

Areas of advanced technology that are either critical or offer significant benefits to the development of future Earth-orbit transportation systems were identified. Technology assessment was based on the application of these technologies to fully reusable, single-stage-to-orbit (SSTO) vehicle concepts with horizontal landing capability. Study guidelines included mission requirements similar to space shuttle, an operational capability begining in 1995, and main propulsion to be advanced hydrogen-fueled rocket engines. Also evaluated was the technical and economic feasibility of this class of SSTO concepts and the comparative features of three operational take-off modes, which were vertical boost, horizontal sled launch, and horizontal take-off with subsequent inflight fueling. Projections of both normal and accelerated technology growth were made. Figures of merit were derived to provide relative rankings of technology areas. The influence of selected accelerated areas on vehicle design and program costs was analyzed by developing near-optimum point designs.

Haefeli, R. C.↗
NASA NTRS1990

Presentation on a Space Acceleration Measurement System (SAMS)

The primary objective of the Space Acceleration Measurement Systems (SAMS) project is to provide an acceleration measurement system capable of serving a wide variety of space experiments. The design of the system being developed under this project takes into consideration requirements for experiments located in the middeck, in the orbiter bay, and in Spacelab. In addition to measuring, conditioning, and recording accelerations, the system will be capable of performing complex calculations and interactive control. The main components consist of a remote triaxial optical storage device. In operation, the triaxial sensor head produces output signals in response to acceleration inputs. These signals are preamplified, filtered and converted into digital data which is then transferred to optical memory. The system design is modular, facilitating both software and hardware upgrading as technology advances. Two complete acceleration measurement flight systems will be build and tested under this project.

Chase, Theodore L.↗
DOE OSTI2021

The CMS Phase-1 Pixel Detector Upgrade

The CMS detector at the CERN LHC features a silicon pixel detector as its innermost subdetector. The original CMS pixel detector has been replaced with an upgraded pixel system (CMS Phase-1 pixel detector) in the extended year-end technical stop of the LHC in 2016/2017. The upgraded CMS pixel detector is designed to cope with the higher instantaneous luminosities that have been achieved by the LHC after the upgrades to the accelerator during the first long shutdown in 2013–2014. Compared to the original pixel detector, the upgraded detector has a better tracking performance and lower mass with four barrel layers and three endcap disks on each side to provide hit coverage up to an absolute value of pseudorapidity of 2.5. This paper describes the design and construction of the CMS Phase-1 pixel detector as well as its performance from commissioning to early operation in collision data-taking.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Competitiveness Improvement Project (CIP)

Through the Competitiveness Improvement Project (CIP), the U.S. DOE supports small businesses who design and manufacture small or medium wind turbine technology through cost-shared subcontracts awarded via a competitive process. The goals of the CIP are to: improve cost competitiveness with other distributed generation technology through optimized designs and advanced manufacturing processes; increase the number of certified small and medium wind turbine designs across a wide range of sizes; and accelerate deployment of improved, certified distributed wind energy technology. NREL manages the projects through a defined period of performance subcontract, providing technical monitoring and coordinating technical assistance from DOE labs.

advanced manufacturing↗
NASA NTRS2002

Optimal Control Design using an H(sub 2) Method for the Glovebox Integrated Microgravity Isolation Technology (G-Limit)

The acceleration environment on the International Space Station (ISS) will likely exceed the requirements of many micro-gravity experiments. The Glovebox Integrated Microgravity Isolation Technology (g-LIMIT) is being built by the NASA Marshall Space Flight Center to attenuate the nominal acceleration environment and provide some isolation for microgravity science experiments. G-LIMIT uses Lorentz (voice-coil) magnetic actuators to isolate a platform for mounting science payloads from the nominal acceleration environment. The system utilizes payload acceleration, relative position, and relative orientation measurements in a feedback controller to accomplish the vibration isolation task. The controller provides current commands to six magnetic actuators, producing the required experiment isolation from the ISS acceleration environment. This paper presents the development of a candidate control law to meet the acceleration attenuation requirements for the g-LIMIT experiment platform. The controller design is developed using linear optimal control techniques for frequency-weighted H(sub 2) norms. Comparison of the performance and robustness to plant uncertainty for this control design approach is included in the discussion.

Calhoun, Philip C.↗
NASA NTRS2003

X-43C Flight Demonstrator Project Overview

The X-43C Flight Demonstrator Project is a joint NASA-USAF hypersonic propulsion technology flight demonstration project that will expand the hypersonic flight envelope for air-breathing engines. The Project will demonstrate sustained accelerating flight through three flights of expendable X-43C Demonstrator Vehicles (DVs). The approximately 16-foot long X-43C DV will be boosted to the starting test conditions, separate from the booster, and accelerate from Mach 5 to Mach 7 under its own power and autonomous control. The DVs will be powered by a liquid hydrocarbon-fueled, fuel-cooled, dual-mode, airframe integrated scramjet engine system developed under the USAF HyTech Program. The Project is managed by NASA Langley Research Center as part of NASA's Next Generation Launch Technology Program. Flight tests will be conducted by NASA Dryden Flight Research Center off the coast of California over water in the Pacific Test Range. The NASA/USAF/industry project is a natural extension of the Hyper-X Program (X-43A), which will demonstrate short duration (approximately 10 seconds) gaseous hydrogen-fueled scramjet powered flight at Mach 7 and Mach 10 using a heavy-weight, largely heat sink construction, experimental engine. The X-43C Project will demonstrate sustained accelerating flight from Mach 5 to Mach 7 (approximately 4 minutes) using a flight-weight, fuel-cooled, scramjet engine powered by much denser liquid hydrocarbon fuel. The X-43C DV design flows from integrating USAF HyTech developed engine technologies with a NASA Air-Breathing Launch Vehicle accelerator-class configuration and Hyper-X heritage vehicle systems designs. This paper describes the X-43C Project and provides the background for NASA's current hypersonic flight demonstration efforts.

Moses, Paul L.↗
DOE OSTI2022

Versatile Test Reactor Conceptual Core Design

The VTR is a 300-MW(thermal) sodium-cooled fast reactor (SFR) designed for the specific purpose of delivering unique testing capabilities to enable the advancement of all reactor technologies. With its flux level, irradiation volume, and operational flexibility, the VTR will enable accelerated testing of materials, fuels, and various components needing irradiation testing. Proven SFR technologies and design approaches have been leveraged in designing the VTR core, ensuring the highest possible readiness level. This resulted in the VTR using ternary metallic fuel and delivering fast flux levels in excess of 4 x 10 15 n/cm 2 ∙ s over large useful volumes, corresponding to about 60 dpa/year in steel. As part of the design efforts, the VTR core performance has been determined for a representative configuration, ensuring that the reactivity control systems offer sufficient shutdown margins, that the core can be safely cooled in all situations, and that reactivity feedback coefficients are conducive to a favorable safety behavior. Furthermore, the incorporation of features such as fuel assembly storage in the shield region supports the flexible and reliable operation of the VTR. Additional design work has been ongoing as well. This includes thorough shielding performance evaluations to ensure safe operation of the VTR, verification and validation of the design tools used to achieve compliance with Nuclear Quality Assurance (NQA-1) requirements, early assessment of the impact of irradiation experiments on the core performance envelope and associated margins, and in-depth uncertainty quantification efforts to quantify the anticipated range of performance characteristics. An experimental program supporting the VTR core design has been set up, with the current focus being on thermal-hydraulic experiments. The purpose of this experimental program is to obtain confirmatory measurements to serve directly as part of the core design basis or as part of the validation cases supporting the simulation tools used.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

A perspective on Bayesian methods applied to materials discovery and design

For more than two decades, there has been increasing interest in developing frameworks for the accelerated discovery and design of novel materials that could enable promising and transformative technologies. The Integrated Computational Materials Engineering (ICME) program called for integrating computational tools to establish linkages along process-structure-property-performance (PSPP) chains. The Materials Genome Initiative called for integrating experiments and computations within data science frameworks as a strategy to accelerate the materials development cycle. While these frameworks and paradigms have been quite influential, traditional ICME or data science-based approaches tend to have some limitations, mainly when querying the materials space is costly and very little information is available. Bayesian methods are more suitable in this context due to their efficiency gains. To this end, the materials discovery problem is framed as a Bayesian Optimization (BO). Different examples in which BO has been applied to solve materials discovery problems are presented. The methods/examples discussed include BO under model uncertainty, multi-information source BO, multi-objective and multi-constraint BO, and batch BO. Bayesian Materials Discovery is a promising area of research that is likely to become more influential as more attention is put on autonomous materials discovery platforms. Therefore, a discussion is provided on the potential development of such methods to increase the ability of existing platforms in materials discovery. Here, the ultimate goal is to pave the way to autonomous materials discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Overview of the LHeC and FCC-he accelerator concepts

The Large Hadron–Electron Collider is designed to move the field of deep inelastic scattering to the energy and intensity frontier of particle physics. Exploiting energy-recovery technology, it collides a novel, intense electron beam with a proton or ion beam from the High-Luminosity Large Hadron Collider. The accelerator and interaction regions are designed for concurrent electron–proton and proton–proton operations. This paper represents the concepts of an updated design study and discusses the design challenges of the project.

Holzer, B. J.↗
DOE OSTI2023

DuraMAT Technology Scouting Report: Assessing Module Reliability Risks Associated with Projected Technological Changes

Maintaining the reliability of photovoltaic (PV) modules in the face of rapidly changing technology is critical to maximizing solar energy's contribution to global decarbonization. Our presentation describes expected changes in PV technology and their impacts on performance and reliability. We leverage PV market reports, interviews with PV researchers and other industry stakeholders, and peer-reviewed literature to narrow the multitude of possible changes into a manageable set of 11 impactful trends likely to be incorporated in near-term crystalline-silicon module designs. We group the trends into four categories (module architecture, interconnect technologies, bifacial modules, and cell technology) and explore the drivers behind the changes, their interactions, and associated reliability risks and benefits. Our analysis identifies specific areas that would benefit from accelerating the PV reliability learning cycle, to assess emerging module products and designs more accurately. We recommend that researchers continue tracking module technologies and their reliability implications so efforts can be focused on the most impactful trends. As the rapid technological turnover continues, it is also critical to incorporate fundamental knowledge into models that can predict module reliability. Predictive capabilities complete the PV reliability learning cycle-reducing the time required to assess new designs and mitigating the risks associated with large-scale deployment of new products.

bifacial↗
DOE OSTI2024

Linac_Gen: Integrating Machine Learning and Particle-in-Cell Methods for Enhanced Beam Dynamics at Fermilab

Here, we introduce Linac_Gen, a tool developed at Fermilab, which combines machine learning algorithms with Particle-in-Cell methods to advance beam dynamics in linacs. Linac_Gen employs techniques such as Random Forest, Genetic Algorithms, Support Vector Machines, and Neural Networks, achieving a tenfold increase in speed for phase-space matching in Linacs over traditional methods, through the use of genetic algorithms. Crucially, Linac_Gen's adept handling of 3D field maps elevates the precision and realism in simulating beam instabilities and resonances, marking a key advancement in the field. Benchmarked against established codes, Linac_Gen demonstrates not only improved efficiency and precision in beam dynamics studies but also in the design and optimization of Linac systems, as evidenced in its application to Fermilab's PIP-II Linac project. This work represents a notable advancement in accelerator physics, marrying ML with PIC methods to set new standards for efficiency and accuracy in accelerator design and research. Linac_Gen exemplifies a novel approach in accelerator technology, offering substantial improvements in both theoretical and practical aspects of beam dynamics.

43 PARTICLE ACCELERATORS↗
NASA NTRS1980

Solar/hydrogen systems assessment. Volume 1: Solar/hydrogen systems for the 1985 - 2000 time frame

Opportunities for commercialization of systems capable of producing hydrogen from solar energy were studied. The hydrogen product costs that might be achieved by the four selected candidate systems was compared with the pricing structure and practices of the commodity gas market. Subsequently, product cost and market price match was noted to exist in the small user sector of the hydrogen marketplace. Barriers to and historical time lags in, commercialization of new technologies are reviewed. Recommendations for development and demonstration programs designed to accelerate the commercialization of the candidate systems are presented.

Foster, R. W.↗
NASA NTRS1990

Control research in the NASA high-alpha technology program

NASA is conducting a focused technology program, known as the High-Angle-of-Attack Technology Program, to accelerate the development of flight-validated technology applicable to the design of fighters with superior stall and post-stall characteristics and agility. A carefully integrated effort is underway combining wind tunnel testing, analytical predictions, piloted simulation, and full-scale flight research. A modified F-18 aircraft has been extensively instrumented for use as the NASA High-Angle-of-Attack Research Vehicle used for flight verification of new methods and concepts. This program stresses the importance of providing improved aircraft control capabilities both by powered control (such as thrust-vectoring) and by innovative aerodynamic control concepts. The program is accomplishing extensive coordinated ground and flight testing to assess and improve available experimental and analytical methods and to develop new concepts for enhanced aerodynamics and for effective control, guidance, and cockpit displays essential for effective pilot utilization of the increased agility provided.

Gilbert, William P.↗
DOE OSTI2024

Linac_Gen: integrating machine learning and particle-in-cell methods for enhanced beam dynamics at Fermilab

Here, we introduce Linac_Gen, a tool developed at Fermilab, which combines machine learning algorithms with Particle-in-Cell methods to advance beam dynamics in linacs. Linac_Gen employs techniques such as Random Forest, Genetic Algorithms, Support Vector Machines, and Neural Networks, achieving a tenfold increase in speed for phase-space matching in linacs over traditional methods through the use of genetic algorithms. Crucially, Linac_Gen's adept handling of 3D field maps elevates the precision and realism in simulating beam instabilities and resonances, marking a key advancement in the field. Benchmarked against established codes, Linac_Gen demonstrates not only improved efficiency and precision in beam dynamics studies but also in the design and optimization of linac systems, as evidenced in its application to Fermilab's PIP-II linac project. This work represents a notable advancement in accelerator physics, marrying ML with PIC methods to set new standards for efficiency and accuracy in accelerator design and research. Linac_Gen exemplifies a novel approach in accelerator technology, offering substantial improvements in both theoretical and practical aspects of beam dynamics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Artificial Intelligence for Autonomous Molecular Design: A Perspective

Domain-aware artificial intelligence has been increasingly adopted in recent years to expedite molecular design in various applications, including drug design and discovery. Recent advances in areas such as physics-informed machine learning and reasoning, software engineering, high-end hardware development, and computing infrastructures are providing opportunities to build scalable and explainable AI molecular discovery systems. This could improve a design hypothesis through feedback analysis, data integration that can provide a basis for the introduction of end-to-end automation for compound discovery and optimization, and enable more intelligent searches of chemical space. Several state-of-the-art ML architectures are predominantly and independently used for predicting the properties of small molecules, their high throughput synthesis, and screening, iteratively identifying and optimizing lead therapeutic candidates. However, such deep learning and ML approaches also raise considerable conceptual, technical, scalability, and end-to-end error quantification challenges, as well as skepticism about the current AI hype to build automated tools. To this end, synergistically and intelligently using these individual components along with robust quantum physics-based molecular representation and data generation tools in a closed-loop holds enormous promise for accelerated therapeutic design to critically analyze the opportunities and challenges for their more widespread application. This article aims to identify the most recent technology and breakthrough achieved by each of the components and discusses how such autonomous AI and ML workflows can be integrated to radically accelerate the protein target or disease model-based probe design that can be iteratively validated experimentally. Taken together, this could significantly reduce the timeline for end-to-end therapeutic discovery and optimization upon the arrival of any novel zoonotic transmission event. Our article serves as a guide for medicinal, computational chemistry and biology, analytical chemistry, and the ML community to practice autonomous molecular design in precision medicine and drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

High-Fidelity Accelerated Design of High-performance Electrochemical Systems

Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and transportation. In both of these areas, new electrochemical materials will be critical, but their development currently relies heavily on human-time-intensive experimental trial and error and computationally expensive first-principles, meso-scale and continuum simulations. To accelerate this process, our team has developed the AutoMat platform. AutoMat can accelerate development of new electrochemical materials along two avenues: first, automated input generation and management of simulations at multiple lengthscales as well as “handoff” of outputs from one lengthscale as inputs to the next; and second, replacement of the most computationally intensive simulation processes with machine-learned surrogate models. The crux of our team’s effort was not “reinventing the wheel” by developing entirely new techniques, but rather building a “superhighway” that allows existing state-of-the-art techniques to run faster and more smoothly than before. AutoMat can utilize tools spanning from first-principles quantum chemistry computations to automated robotic experimentation, and is driven by design space search techniques to reduce the number of iterations through the full simulation loop by rapidly targeting promising regions of design spaces such as single-atom alloy catalysts or blends of liquid electrolytes.

25 ENERGY STORAGE↗